ComfyUI's ControlNet Auxiliary Preprocessors
Plug-and-play ComfyUI node sets for making ControlNet hint images.
Quick Technical Summary: ComfyUI's ControlNet Auxiliary Preprocessors
- Base VRAM Footprint:
- 2048 MB (6 GB Tier)
- Primary Dependencies:
- addict, albumentations, einops, filelock, ftfy, fvcore, huggingface_hub, importlib_metadata, matplotlib, mediapipe>=0.8.0, numpy, omegaconf, onnxruntime-gpu, opencv-python, pillow, python-dateutil, pyyaml, scikit-image, scikit-learn, scipy, torch, torchvision, trimesh, yacs, yapf, yapf
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/Fannovel16/comfyui_controlnet_aux
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does ComfyUI's ControlNet Auxiliary Preprocessors require?
Direct Answer: The ComfyUI node ComfyUI's ControlNet Auxiliary Preprocessors requires a minimum base VRAM of 2048MB and is optimized for GPUs with at least 6GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 2048MB (2.0GB)
- Recommended GPU:
- 6GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- HIGH
Cheapest VRAM Upgrade Paths (Live Market Prices):
- GeForce RTX 3060 12GB (Ultimate Budget VRAM King)──► Used: $209.62View eBay ↗
- GeForce RTX 4060 8GB (Modern Entry-Level)──► New: $303.50View Amazon ↗
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
Verify Compatibility for Your Specific GPU VRAM
Select your graphics card's VRAM capacity to view optimized batch sizes, suggested resolutions, and custom performance tips for ComfyUI's ControlNet Auxiliary Preprocessors:
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What Python packages are required for ComfyUI's ControlNet Auxiliary Preprocessors?
Direct Answer: Running ComfyUI's ControlNet Auxiliary Preprocessors requires installing the following Python package dependencies: addict, albumentations, einops, filelock, ftfy, fvcore, huggingface_hub, importlib_metadata, matplotlib, mediapipe>=0.8.0, numpy, omegaconf, onnxruntime-gpu, opencv-python, pillow, python-dateutil, pyyaml, scikit-image, scikit-learn, scipy, torch, torchvision, trimesh, yacs, yapf, yapf. Ensure your ComfyUI environment has these packages active before launching.
addict
albumentations
einops
filelock
ftfy
fvcore
huggingface_hub
importlib_metadata
matplotlib
mediapipe>=0.8.0
numpy
omegaconf
onnxruntime-gpu
opencv-python
pillow
python-dateutil
pyyaml
scikit-image
scikit-learn
scipy
torch
torchvision
trimesh
yacs
yapf
yapfInteractive Setup & Dependency Resolver
# Loading command...Frequently Asked Questions
How much VRAM does ComfyUI's ControlNet Auxiliary Preprocessors require?
ComfyUI's ControlNet Auxiliary Preprocessors requires a minimum of 2048MB (2.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 6GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.
Can I run ComfyUI's ControlNet Auxiliary Preprocessors on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 8.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 8.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 12.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 19.6GB headroom
How much VRAM does ComfyUI's ControlNet Auxiliary Preprocessors take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), ComfyUI's ControlNet Auxiliary Preprocessors runs smoothly on an RTX 3060 (12GB) with 8.8GB of headroom. This is sufficient to run the node alongside standard SD 1.5 and SDXL workflows in full precision. On an RTX 4090 (24GB VRAM), the node runs with extreme headroom on an RTX 4090 (24GB) with 19.6GB of dedicated headroom. This allows you to combine the node with massive models (like FLUX.1 Dev, Schnell, or Hunyuan Video) in full precision (FP16) without any offload flags.
What PyTorch version does ComfyUI's ControlNet Auxiliary Preprocessors need?
ComfyUI's ControlNet Auxiliary Preprocessors requires the following PyTorch-related packages: torch, torchvision. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).
What Python packages are required for ComfyUI's ControlNet Auxiliary Preprocessors?
To run ComfyUI's ControlNet Auxiliary Preprocessors, you need to install: addict, albumentations, einops, filelock, ftfy, fvcore, huggingface_hub, importlib_metadata, matplotlib, mediapipe>=0.8.0, numpy, omegaconf, onnxruntime-gpu, opencv-python, pillow, python-dateutil, pyyaml, scikit-image, scikit-learn, scipy, torch, torchvision, trimesh, yacs, yapf, yapf. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running ComfyUI's ControlNet Auxiliary Preprocessors?
ComfyUI's ControlNet Auxiliary Preprocessors supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.
How do I install ComfyUI's ControlNet Auxiliary Preprocessors in ComfyUI?
To install ComfyUI's ControlNet Auxiliary Preprocessors: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/Fannovel16/comfyui_controlnet_aux, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.